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摘要翻译：
通过网络搜索渠道创建和监测具有竞争力和成本效益的按点击付费广告活动是一项需要专门知识和努力的资源任务。协助甚至自动化广告专家的工作将具有无与伦比的商业价值。在本文中，我们提出了一个方法，一个体系结构，和一个完全功能的框架，用于半自动化和完全自动化的创建，监控，和优化具有成本效益的按点击付费活动，并有预算限制。所述活动创建模块基于扩展有相应广告文本的所述待广告网页的内容自动生成关键词。这些关键字用于自动创建完全配备了适当值集的活动。这些活动被上传到拍卖平台并开始运行。优化模块侧重于从现有的活动统计数据和以前各期的应用战略中学习过程，以便在下一个时期进行最佳投资。目标是在当前预算限制下最大限度地提高性能（即点击、动作）。在真实世界的Google AdWords活动中，对功能完备的原型进行了实验评估，并在活动性能统计方面呈现了一种有希望的行为，因为它系统地优于竞争的手动维护的活动。
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英文标题：
《Toward an Integrated Framework for Automated Development and
Optimization of Online Advertising Campaigns》
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作者：
Stamatina Thomaidou, Michalis Vazirgiannis, Kyriakos Liakopoulos
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最新提交年份：
2012
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分类信息：
一级分类：Computer Science 计算机科学
二级分类：Information Retrieval 信息检索
分类描述：Covers indexing, dictionaries, retrieval, content and analysis. Roughly includes material in ACM Subject Classes H.3.0, H.3.1, H.3.2, H.3.3, and H.3.4.
涵盖索引，字典，检索，内容和分析。大致包括ACM主题课程H.3.0、H.3.1、H.3.2、H.3.3和H.3.4中的材料。
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一级分类：Computer Science 计算机科学
二级分类：Artificial Intelligence 人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
Creating and monitoring competitive and cost-effective pay-per-click advertisement campaigns through the web-search channel is a resource demanding task in terms of expertise and effort. Assisting or even automating the work of an advertising specialist will have an unrivaled commercial value. In this paper we propose a methodology, an architecture, and a fully functional framework for semi- and fully- automated creation, monitoring, and optimization of cost-efficient pay-per-click campaigns with budget constraints. The campaign creation module generates automatically keywords based on the content of the web page to be advertised extended with corresponding ad-texts. These keywords are used to create automatically the campaigns fully equipped with the appropriate values set. The campaigns are uploaded to the auctioneer platform and start running. The optimization module focuses on the learning process from existing campaign statistics and also from applied strategies of previous periods in order to invest optimally in the next period. The objective is to maximize the performance (i.e. clicks, actions) under the current budget constraint. The fully functional prototype is experimentally evaluated on real world Google AdWords campaigns and presents a promising behavior with regards to campaign performance statistics as it outperforms systematically the competing manually maintained campaigns.
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PDF链接：
https://arxiv.org/pdf/1208.1187
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